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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Nonstationary and Non-Gaussian Moving Average Model for Solar Irradiance

Historically, power has flowed from large power plants to customers. Increasing penetration of distributed energy resources such as solar power from rooftop photovoltaic has made the distribution network a two-way-street with power being generated at the customer level. The incorporation of renewables introduces additional uncertainty and variability into the power grid. Distribution network operation studies are being adapted to include renewables; however, such studies require high quality solar irradiance data that adequately reflect realistic meteorological variability. Data from satellite-based products are spatially complete, but temporally coarse, whereas solar irradiances exhibit high frequency variation at very fine timescales. We propose a new stochastic method for temporally downscaling global horizontal irradiance (GHI) to 1 min resolution, but we do not consider the spatial aspect due to limited availability of the in situ irradiance measurements. Solar irradiance's first and second-order structures vary diurnally and seasonally, and our model adapts to such nonstationarity. Empirical irradiance data exhibits highly non-Gaussian behavior; we develop a nonstationary and non-Gaussian moving average model that is shown to capture realistic solar variability at multiple timescales. We also propose a new estimation scheme based on Cholesky factors of empirical autocovariance matrices, bypassing difficult and inaccessible likelihood-based approaches. The model is demonstrated for a case study of three locations that are located in diverse climates through the United States. The model is compared against competitors from the literature and is shown to provide better uncertainty and variability quantification on testing data.

Cholesky factor↗
DOE OSTI2018

Innovative thermal distillation method using solar heat localization

The thermal distillation uses energy to evaporate water and subsequently condense the vapor to liquid form. Waste energy from industrial processes, electricity, or solar energy are the examples of an input energy for thermal distillation systems. In this paper, we have designed, fabricated, and tested an eco-friendly and low- cost distillation system which uses solar heat localization for evaporation of water and later condense the vapor back to liquid as liquid water. The unique feature of this method is the high rate of evaporation when compared to other thermal solar distillation/desalination systems. In this method, the incoming heat is confined to the porous media where bottom layer acts a porous insulator. The capillary force in the porous structure pumps up the liquid water to the hot surface, within the porous medium, where liquid heats up and changes to vapor phase. Since there is no moving part in this method, and due to its independency to electricity, it a great candidate for deployment in remote areas that access to grid power is limited and maintenance is not feasible.

Jaladi, Divya↗
DOE OSTI2014

Efficient algorithm for locating and sizing series compensation devices in large power transmission grids: I. Model implementation

We explore optimization methods for planning the placement, sizing and operations of Flexible Alternating Current Transmission System (FACTS) devices installed to relieve transmission grid congestion. We limit our selection of FACTS devices to Series Compensation (SC) devices that can be represented by modification of the inductance of transmission lines. Our master optimization problem minimizes the l 1 norm of the inductance modification subject to the usual line thermal-limit constraints. We develop heuristics that reduce this non-convex optimization to a succession of Linear Programs (LP) which are accelerated further using cutting plane methods. The algorithm solves an instance of the MatPower Polish Grid model (3299 lines and 2746 nodes) in 40 seconds per iteration on a standard laptop—a speed up that allows the sizing and placement of a family of SC devices to correct a large set of anticipated congestions. We observe that our algorithm finds feasible solutions that are always sparse, i.e., SC devices are placed on only a few lines. In a companion manuscript, we demonstrate our approach on realistically-sized networks that suffer congestion from a range of causes including generator retirement. In this manuscript, we focus on the development of our approach, investigate its structure on a small test system subject to congestion from uniform load growth, and demonstrate computational efficiency on a realistically-sized network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2024

SEAS Communication Engine: An Extensible, Flexible Wrapper for Co-Simulation Agents

When modeling and analyzing the power grid and other large scale systems, researchers often express scenarios as optimization problems and feed them into advanced software solvers. In order to allow multiple solvers to communicate with each other and share data from different domains, the National Renewable Energy Laboratory (NREL) and associated Department of Energy (DOE) labs have developed a software framework called the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS). HELICS allows cosimulation via a collection of client libraries for different languages that can be called from the appropriate optimization software. However, these client libraries do not provide a higher level of abstraction beyond reading and writing data off of the shared HELICS bus. In this paper, we describe a new software library called the SEAS Communication Engine that exposes a higher-level API for running cosimulation problems. The SEAS Engine provides a class-based abstraction on top of the Python HELICS client, in order to allow users to implement their domain-specific cosimulations without needing to interact with core HELICS primitives. This will make adoption of HELICS and cosimulation in general easier, by exposing a simpler API. In the second part of the paper, we validate our library on a collection of different simulation examples, including the canonical IEEE 13 Bus Feeder. Lastly, we demonstrate using the SEAS Engine to directly call domain-specific code written in the Julia programming language. Our hope is that this will serve as a template for easily calling software in different programming languages via the SEAS Engine, thereby avoiding code duplication and complexity.

co-simulation↗
DOE OSTI2018

Institutional influence on power sector investments: A case study of on- and off-grid energy in Kenya and Tanzania

With the recent decline of renewable energy technology costs—most notably solar photovoltaics —off-grid energy systems are becoming increasingly attractive alternatives to grid extension for advancing rural electrification in Africa. However, there are institutional challenges to wider adoption of off-grid solutions. Combining a multi-level perspective with project funding data from the Kenyan and Tanzanian energy sectors, we assess the extent to which these new off-grid technologies have been incorporated into the existing energy regimes in both countries. Using a qualitative assessment of academic literature and official documents, and a quantitative assessment of energy investments, we find that although international development agencies have provided financial support for niche, off-grid companies, both global donors and the regime electricity sector operators in Kenya and Tanzania continue to favor on-grid and grid extension activities. While landscape influences on both countries are similar, we find that differences within the institutional regimes result in different development pathways for off-grid niches. In Kenya, unbundling and privatization efforts have attracted private investment in both on- and off-grid projects. Finally, Tanzania has more relaxed regulations for off-grid power producers, and a clearer regulatory framework for allowing off-grid operators to impose cost-reflective tariffs, which creates a supportive environment for niche innovation.

13 HYDRO ENERGY↗
DOE OSTI2021

PMU-data-driven Event Classification in Power Transmission Grids

This paper presents an event classification in transmission grids. The convolutional neural network (CNN)-based classifier is proposed to capture the temporal similarity of time-synchronized data stream from phasor measurement units (PMUs). The proposed CNN is trained using Bayesian optimization to search for the best hyperparameters. The effectiveness of the proposed event classification is validated through the real-world dataset from the U.S. transmission grids. This dataset includes line outage, transformer outage, frequency, and oscillation events. The validation process also includes different PMU outputs, such as voltage magnitude, phase angle, current magnitude, frequency, and rate of change of frequency (ROCOF). The results show that ROCOF gives the best classification performance compared to other PMU outputs. In addition, it is shown that the classifier trained with a larger dataset has higher accuracy. Moreover, the superiority of the proposed method is validated through comparison with other state-of-the-art classification methods.

Niazazari, Iman↗
DOE OSTI2023

Trust Model System for the Energy Grid of Things Network Communications

Network communication is crucial in the Energy Grid of Things (EGoT). Without a network connection, the energy grid becomes just a power grid where the energy resources are available to the customer uni-directionally. A mechanism to analyze and optimize the energy usage of the grid can only happen through a medium, a communications network, that enables information exchange between the grid participants and the service provider. Security implementers of EGoT network communication take extraordinary measures to ensure the safety of the energy grid, a critical infrastructure, as well as the safety and privacy of the grid participants. With the dynamic nature of network communication of the EGoT, the information provided by the customer or the service provider can be falsified by a malicious attacker. Therefore, a trust model is necessary to monitor any abnormal activities. This paper describes a distributed trust model system that meets the need of the EGoT. This paper describes methods for evaluating and improving the distributed trust model using standard hypothesis testing metrics such as true positive, false positive, true negative, false negative, equal error rate, and F1 score. Example calculations are shown based on generated sample data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Optimal Water-Power Flow Problem: Formulation and Distributed Optimal Solution

This paper formalizes an optimal water-power flow (OWPF) problem to optimize the use of controllable assets across power and water systems while accounting for the couplings between the two infrastructures. Tanks and pumps are optimally managed to satisfy water demand while improving power grid operations; {for the power network, an AC optimal power flow formulation is augmented to accommodate the controllability of water pumps.} Unfortunately, the physics governing the operation of the two infrastructures and coupling constraints lead to a nonconvex (and, in fact, NP-hard) problem; however, after reformulating OWPF as a nonconvex, quadratically-constrained quadratic problem, a feasible point pursuit-successive convex approximation approach is used to identify feasible and optimal solutions. In addition, a distributed solver based on the alternating direction method of multipliers enables water and power operators to pursue individual objectives while respecting the couplings between the two networks. The merits of the proposed approach are demonstrated for the case of a distribution feeder coupled with a municipal water distribution network.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data and price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Chapter 11: Marine and Hydrokinetic Power Generation and Power Plants

Marine and hydrokinetic (MHK) power generation is a relatively new type of renewable generation. Predecessors such as wind power generation, hydropower plant generation, geothermal generation, photovoltaic generation, and solar thermal generation have gained a lot of attention because of their successful implementation. The successful integration of renewable generation into the electric power grid has energized the power system global communities to take the lessons learned, innovations, and market structure to focus on the large potential of MHK to also contribute to the pool of renewable energy generation. This chapter covers the broad spectrum of MHK generation. The state-of-the-art power takeoff methods will be discussed. Types of electrical generators will be presented, and the options for implementation will be presented.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Center for Efficiency in Sustainable Energy Systems

The main goal of the Center for Efficiency in Sustainable Energy Systems is to produce a methodology that evaluates a variety of energy systems. Task I. Improved Energy Efficiency for Industrial Processes: This task, completed in partnership with area manufacturers, analyzes the operation of complex manufacturing facilities to provide flexibilities that allow them to improve active-mode power efficiency, lower standby-mode power consumption, and use low cost energy resources to control energy costs in meeting their economic incentives; (2) Identify devices for the efficient transformation of instantaneous or continuous power to different devices and sections of industrial plants; and (3) use these manufacturing sites to demonstrate and validate general principles of power management. Task II. Analysis of a solid oxide fuel cell operating on landfill gas: This task consists of: (1) analysis of a typical landfill gas; (2) establishment of a comprehensive design of the fuel cell system (including the SOFC stack and BOP), including durability analysis; (3) development of suitable reforming methods and catalysts that are tailored to the specific SOFC system concept; and (4) SOFC stack fabrication with testing to demonstrate the salient operational characteristics of the stack, including an analysis of the overall energy conversion efficiency of the system. Task III. Demonstration of an urban wind turbine system: This task consists of (1) design and construction of two side-by-side wind turbine systems on the YSU campus, integrated through power control systems with grid power; (2) preliminary testing of aerodynamic control effectors (provided by a small business partner) to demonstrate improved power control, and evaluation of the system performance, including economic estimates of viability in an urban environment; and (3) computational analysis of the wind turbine system as an enabling activity for development of smart rotor blades that contain integrated sensor/actuator/controller modules to enhance energy capture and reduce aerodynamic loading and noise by way of virtual aerodynamic shaping. Accomplishments: Task I. Improved Energy Efficiency for Industrial Processes: We organized an energy management training session held on February 22, 2011, which was advertised through a regional manufacturing association to provide wide-ranging notification. Over two dozen companies were represented a the seminar, ranging from heavy manufacturing businesses with $5,000,000 per year energy expenses, to small, light manufacturing facilities. Task 2. Landfill Fuel Cell Power Generation Solid Oxide Fuel Cells (SOFCs) were constructed and evaluated as a means of obtaining electrical energy from landfill gas. Analysis of landfill gas. Attempts at collecting gas samples at the landfill and evaluating them on campus were still unsuccessful. Even a Teflon® sample bag would lose its H2S content. Evaluation of Gas Clean-up We consider this a confirmation of the CO2 effect on the solubility of H2S in water making much less sulfide available for the photocatalyst. It also means that another method should be employed to clean up landfill gas. Nonetheless, composition of impurities in landfill gas was reduced sufficiently to allow successful operation of the test fuel cell. Comparison to a PEM fuel cell system. If a PEMFC were to be operated with landfill gas as the fuel, the gas would have to be treated for sulfur removal, and then processed in a reformer large enough to drive the equilibrium far toward the products, so that negligible CO would flow into the fuel cell. Analysis of a fuel cell running on landfill gas. Using a Gow-Mac gas chromatograph with a thermal conductivity detector, unambiguous determination of CO can be made, at least as a primary constituent Task 3: Task 3 Plasma Controlled Turbine Blades Wind Turbine Selection. After carefully reviewing the various model available in the market the team selected the ARE 110 (2.5kW). The ARE 110 provides a very long life with little maintenance due to their relatively low rotational speeds (low RPM). The turbines large swept area (10.2ms2/110sq.ft), high-efficiency blades, purpose built alternator, and optimized power electronics ensure maximum energy capture from a wide range of wind speeds. Two wind turbines were installed side-by-side at the Melnick Hall site to compare their performance. Evaluate and Optimize Aerodynamically Enhanced Turbine Blades Due to delays in the installation of the wind turbines, no actual data was obtained within the contract period. At this time, the turbines are installed and operational at YSU with standard blades. We are in contact with Orbital Research and in discussion as to how best the required data can be obtained.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

HEMP Transformer Defense Through Power Electronics

High altitude electromagnetic pulses and geo-magnetic disturbances have the potential to severely impact the electric power grid by damaging large power transformers and causing severe power quality issues. This impact comes as a result of a quasi-static bias induced on transmission lines by geomagnetically induced currents which saturate magnetic components in the electric power system. This paper introduces the concept of utilizing a h-bridge inverter on the neutral of a LPT to inject a DC bias equivalent voltage onto the neutral side of the transformer windings. This biasing floats the transformer windings, eliminating the effect of the DC current and keeping the transformer from saturating. Schematic diagrams will be presented, along with simulation model data using Typhoon and PLECS, and finally test results from a benchtop hardware test.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

NREL Overview of Grid-Tied Power Electronics

This presentation focuses on the power electronics related research efforts carried out by researchers at the Power Systems Engineering Center at NREL.

24 POWER TRANSMISSION AND DISTRIBUTION↗